Analysis Of The Characteristics Of The Atmospheric Pollution In Hohhot-Baotou-Erdos Urban Agglomeration

Along with the rapid processing of urbanization, industrialization and regional economic integration in China, the city scale expands unceasingly, and the mutual effect of pollution between the cities is becoming more and more obvious. Urban agglomeration is the population concentration, intensive industry and relatively developed area of economy, and at the same time it is also the worst-hit area of environmental pollution. Hohhot-Baotou-Erdos urban agglomeration (Hohhot, Baotou and Erdos) is the area that has the most concentrated population, the most developed economy, and the highest industrialization and urbanization in Inner Mongolia autonomous, and it is also one of relatively developed urban agglomerations about economy in China.Based on air quality and the primary pollutants, concentration data of six pollutants (SO2, NO2, PM10, PM2.5, CO and O3), meteorological factors (temperature, pressure, wind speed and relative humidity) data and the visibility data in Hohhot-Baotou-Erdos, this article studied air quality situation, spatial and temporal distribution of pollutants and the relationship with meteorological factors. And further research on the relationship between visibility and influence factors, the relationship between the O3 and precursors were also accomplished. The main conclusions were as follows:(1) The emissions of SO2, NOx, smoke (power) dust were Erdos>Baotou>Hohhot Overall air quality condition was Erdos (better)>Hohhot (better)>Baotou, and the ratio of fine days was 82.8%,72.7% and 61.2% respectively. The main pollutant affecting the Hohhot and Baotou was PM10, while O3 was in Erdos.(2) Study via Daniel trend analysis on the annual concentration of SO2,NO2 and PM10 in 2011-2015 in Hohhot-Baotou-Erdos indicated that SO2 and NO2 had significantly declining trend in Erdos, while others were not obvious. From the seasonal variation characteristics, PM10 polluted air seriously in spring and O3 was in summer, while the concentration of PM2.5, SO2, NO2, CO and PM2.5/PM10 was highest in winter and fall and lower in summer and spring. Diurnal variation characteristics of PM10, PM2.5, SO2, NO2 and CO showed bimodal distribution that the first peak appeared generally in 9 am to 11 am and the second peak appeared in 20-23 pm, while O3 showed unimodal distribution which the peak value appeared in about 4 pm. From the spatial distribution, Baotou was the most polluted city by PM10, PM2.5, SO2, NO2, and CO, while O3 was the most serious pollutant in Erdos.(3) Meteorological factors (temperature, pressure, relative humidity, and wind speed) had good correlation with six pollutants concentration. SO2,NO2, PM10, PM2.5 and CO had positive correlation with average pressure and relative humidity and they were negatively related with the average temperature and average wind speed. The correlation of meteorological factors and O3 was opposite to the rest pollutants.(4) Daily variation characteristics of visibility showed bimodal distribution. The visibility was higher in spring and summer, and lower in autumn and winter, also visibility in Hohhot was lower than the other two cities. Visibility had negative correlation with 6 pollutants and the correlation with PM2.5 was first-rate. Visibility was positively correlated with mean air pressure and mean wind speed. And it was negatively correlated with the average temperature and relative humidity, also the correlation between the relative humidity and visibility was first-rate. Multivariate stepwise regression analysis on visibility and each influence factor indicated multiple correlation coefficient of regression equation is> 0.8, which could well predict the actual value of visibility.(5) Daily average concentration of ozone with its precursors (NO, NO2, NOx and CO) had significantly negative correlation under annual scale in 3 cities. From the seasonal variation characteristics, O3 and precursor showed significant positive correlation in summer, while negative correlation in winter. Correlation between O3 hour’s value and NO was not obvious in Erdos, but the rest were characterized by significant negative correlation. Correlation between O3 and its precursor substance in summer was better than other seasons. Atmospheric oxidants OX was significantly positive correlated with O3, while correlation was best in summer and poor correlation appeared in winter.